Double precision exaflop/second has been the traditional definition of general purpose exaflop supercomputer. There are domain-specific machines and even the American DoE Summit and Sierra ...

Arm Holdings has announced that the next revision of its ArmV8-A architecture will include support for bfloat16, a floating point format that is increasingly being used to accelerate machine learning ...

Engineers targeting DSP to FPGAs have traditionally used fixed-point arithmetic, mainly because of the high cost associated with implementing floating-point arithmetic. That cost comes in the form of ...

Most AI chips and hardware accelerators that power machine learning (ML) and deep learning (DL) applications include floating-point units (FPUs). Algorithms used in neural networks today are often ...

Although something that’s taken for granted these days, the ability to perform floating-point operations in hardware was, for the longest time, something reserved for people with big wallets. This ...